Use of motion data in the processing of automotive radar image processing

ABSTRACT

In an example method, a vehicle configured to operate in an autonomous mode could have a radar system used to aid in vehicle guidance. The method could include a plurality of antennas configured to transmit and receive electromagnetic signals. The method may also include a one or more sensors configured to measure a movement of the vehicle. A portion of the method may be performed by a processor configured to: i) determine adjustments based on the movement of the vehicle; ii) calculate distance and direction information for received electromagnetic signals; and iii) recover distance and direction information for received electromagnetic signals with the adjustments applied. The processor may be further configured to adjust the movement of the autonomous vehicle based on the distance and direction information with adjustments applied.

BACKGROUND

Unless otherwise indicated herein, the materials described in thissection are not prior art to the claims in this application and are notadmitted to be prior art by inclusion in this section.

A vehicle could be any wheeled, powered vehicle and may include a car,truck, motorcycle, bus, etc. Vehicles can be utilized for various taskssuch as transportation of people and goods, as well as many other uses.

Some vehicles may be partially or fully autonomous. For instance, when avehicle is in an autonomous mode, some or all of the driving aspects ofvehicle operation can be handled by a vehicle control system. In suchcases, computing devices located onboard and/or in a server networkcould be operable to carry out functions such as planning a drivingroute, sensing aspects of the vehicle, sensing the environment of thevehicle, and controlling drive components such as steering, throttle,and brake. Thus, autonomous vehicles may reduce or eliminate the needfor human interaction in various aspects of vehicle operation.Additionally, some sensing features may be used in conjunction with ahuman-drive mode.

SUMMARY

In a first aspect, an vehicle apparatus is provided. In someembodiments, the vehicle may be an autonomous vehicle. However, in otherembodiments the vehicle may be human controlled. In yet furtherembodiments, the vehicle may be controlled by a combination of human andautonomous control. The vehicle may include an antenna configured tofunction as a portion of a radar system. The antennas may function toboth transmit and receive radio signals. Additionally, the vehicle isconfigured with at least one sensor configured to provide an outputbased on the motion of the vehicle. The radar system receives both thereceived radio signals and the output relating to the motion of thevehicle. The apparatus also includes a processor in the radar systemconfigured to: i) calculate a movement parameter based on the motion ofthe vehicle; and ii) recover the distance and direction information fromthe received radio signal based on the movement parameter.

In a second aspect, a method is provided. The method includes receiving,from at least one antenna, radio signals providing distance anddirection information for at least one object in an environment of theautonomous vehicle. The method also includes receiving, from at leastone sensor, data relating to the motion of the vehicle. The methodfurther includes a processor calculating a movement parameter based onthe motion of the vehicle. The method yet further includes the processorrecovering distance and direction information from the received radiosignal based on the movement parameter. The distance and directioninformation may relate to a target within a field of view of the system.

In a third aspect, an article of manufacture including a tangiblenon-transitory computer-readable medium having stored instructions isprovided. The instructions are executable by a computer system to causethe computer system to perform functions. The functions includereceiving, from at least one antenna, radio signals providing distanceand direction information for at least one object in an environment ofthe autonomous vehicle. The functions also include receiving, from atleast one sensor, data relating to the motion of the vehicle. Thefunctions further include a processor a movement parameter based on themotion of the vehicle. The functions yet further include the processorrecovering distance and direction information from the received radiosignal based on the movement parameter. The distance and directioninformation may relate to a target within a field of view of the system.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the figures and the followingdetailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a vehicle, accordingto an example embodiment.

FIG. 2 shows a vehicle, according to an example embodiment.

FIG. 3 is a top view of an autonomous vehicle operating scenario,according to an example embodiment.

FIG. 4 shows a method, according to an example embodiment.

FIG. 5 is a schematic diagram of a computer program product, accordingto an example embodiment.

DETAILED DESCRIPTION

Example methods and systems are described herein. Any example embodimentor feature described herein is not necessarily to be construed aspreferred or advantageous over other embodiments or features. Theexample embodiments described herein are not meant to be limiting. Itwill be readily understood that certain aspects of the disclosed systemsand methods can be arranged and combined in a wide variety of differentconfigurations, all of which are contemplated herein.

Furthermore, the particular arrangements shown in the Figures should notbe viewed as limiting. It should be understood that other embodimentsmay include more or less of each element shown in a given Figure.Further, some of the illustrated elements may be combined or omitted.Yet further, an example embodiment may include elements that are notillustrated in the Figures.

1. Overview

Example embodiments disclosed herein relate to radar systems in anautonomous vehicle. Some methods disclosed herein could be carried outin part or in full by a vehicle configured to operate in an autonomousmode with or without external interaction (e.g., such as from a user ofthe vehicle). Further, the embodiments disclosed herein may also be usedto help optimize the radar system based on the movement of theautonomous vehicle.

The radar system of the autonomous vehicle may feature a plurality ofantennas. Each antenna may be configured to (i) transmit electromagneticsignals, (ii) receive electromagnetic signals, or (iii) both transmitand receive electromagnetic signals. The antennas may form an array ofantenna elements. The array may be able to steer a beam formed by thetransmitted electromagnetic signals. Additionally, the array may aid indetecting the direction from which electromagnetic signals are received.

The radar system further contains a processor configured to process thereceived signals. The received signals may be reflected from objectswithin the field of view of the radar system. The reflected signals maybe stored as data for processing by the radar system. The processor maybe configured to located objects within the field of view of the radarsystem. For example, the processor in the radar system may calculate adistance and a direction to one or more objects within the field of viewof the radar system.

Additionally, the autonomous vehicle may have one or moreoutput-indication sensors configured to measure a movement of thevehicle. Such output-indication sensors could include, for example,sensors that monitor the wheel speed of the vehicle, the steeringposition, and/or the current location of the vehicle (e.g., a GlobalPositioning System).

Within the context of the disclosure, the processor in the radar systemmay use data associated with the output-indication sensors to adjust thedetermination of the distance and the direction to each object withinthe field of view of the radar system. Depending on the embodiment, theprocessor may compensate for an acceleration of the vehicle. Inparticular, a sudden acceleration or deceleration may cause the pitch ofthe autonomous vehicle to vary. This quick change in pitch may introduceerrors into radar system through a distortion in the received signals.Additionally, if the vehicle is turning, the vehicle may have anassociated pitch and yaw from turning. This quick change in pitch andyaw may also introduce errors into radar system through a distortion inthe received signals. Further, errors may be introduced into radarsystem through a distortion in the received signals caused by a speed ofthe vehicle. For example, when traveling at 25 miles per hour, thevehicle may have a vibration that introduces errors.

Additionally, the vehicle could be operated in a safety mode. The safetymode could represent an autonomous, semi-autonomous, or manual mode inwhich the vehicle may be controlled to operate in a safe fashion. Suchsafety modes of operation could include the vehicle autonomously pullingover to the side of a road and/or the vehicle returning some or alloperational control of the vehicle to a driver or another controlsystem.

A server, such as one or more nodes of a server network, couldadditionally or alternatively carry out the methods disclosed herein inpart or in full. In an example embodiment, a server or computer mayreceive both (i) data associated with the output-indication sensors and(ii) data related to the received signals. Such data associated with theoutput-indication sensors could include any current parameters of thevehicle (e.g., velocity, acceleration, steering position). Further, theserver may already know (or be able to calculate) information related tothe current parameters. Further, the server may also receive (or alreadyhave stored) the data related to the received signals.

The server may be able to calculate a radar adjustment value for theoperation of the radar based on the data associated with theoutput-indication sensors and the data related to the received signals.The server may the use the calculated radar adjustment in furthercalculations. These further calculations may include, but are notlimited to, calculation of revised the distance and directioninformation from the based on data associated with the output-indicationsensors.

Also disclosed herein are non-transitory computer readable media withstored instructions. The instructions could be executable by a computingdevice to cause the computing device to perform functions similar tothose described in the aforementioned methods.

It is understood that there are many different specific methods andsystems that could be used in an unambiguous angle calculation for theradar system. These specific methods and systems are contemplatedherein, and several example embodiments are described below.

2. Example Systems

Example systems within the scope of the present disclosure will now bedescribed in greater detail. An example system may be implemented in ormay take the form of an automobile. However, an example system may alsobe implemented in or take the form of other vehicles, such as cars,trucks, motorcycles, buses, boats, airplanes, helicopters, lawn mowers,earth movers, boats, snowmobiles, aircraft, recreational vehicles,amusement park vehicles, farm equipment, construction equipment, trams,golf carts, trains, and trolleys. Other vehicles are possible as well.

FIG. 1 is a functional block diagram illustrating a vehicle 100,according to an example embodiment. The vehicle 100 could be configuredto operate fully or partially in an autonomous mode. For example, acomputer system could control the vehicle 100 while in the autonomousmode, and may be operable to transmit a radio signal, receive reflectedradio signals with at least one antenna in the radar system, process thereceived reflected radio signals, locate the objects that caused thereflections, calculate an angle and a distance to each object thatreflected the radio signal, and calculate an unambiguous angleassociated with the angle. While in autonomous mode, the vehicle 100 maybe configured to operate without human interaction.

The vehicle 100 could include various subsystems such as a propulsionsystem 102, a sensor system 104, a control system 106, one or moreperipherals 108, as well as a power supply 110, a computer system 112, adata storage 114, and a user interface 116. The vehicle 100 may includemore or fewer subsystems and each subsystem could include multipleelements. Further, each of the subsystems and elements of vehicle 100could be interconnected. Thus, one or more of the described functions ofthe vehicle 100 may be divided up into additional functional or physicalcomponents, or combined into fewer functional or physical components. Insome further examples, additional functional and/or physical componentsmay be added to the examples illustrated by FIG. 1.

The propulsion system 102 may include components operable to providepowered motion for the vehicle 100. Depending upon the embodiment, thepropulsion system 102 could include an engine/motor 118, an energysource 119, a transmission 120, and wheels/tires 121. The engine/motor118 could be any combination of an internal combustion engine, anelectric motor, steam engine, Stirling engine. Other motors and/orengines are possible. In some embodiments, the engine/motor 118 may beconfigured to convert energy source 119 into mechanical energy. In someembodiments, the propulsion system 102 could include multiple types ofengines and/or motors. For instance, a gas-electric hybrid car couldinclude a gasoline engine and an electric motor. Other examples arepossible.

The energy source 119 could represent a source of energy that may, infull or in part, power the engine/motor 118. Examples of energy sources119 contemplated within the scope of the present disclosure includegasoline, diesel, other petroleum-based fuels, propane, other compressedgas-based fuels, ethanol, solar panels, batteries, and other sources ofelectrical power. The energy source(s) 119 could additionally oralternatively include any combination of fuel tanks, batteries,capacitors, and/or flywheels. The energy source 118 could also provideenergy for other systems of the vehicle 100.

The transmission 120 could include elements that are operable totransmit mechanical power from the engine/motor 118 to the wheels/tires121. The transmission 120 could include a gearbox, a clutch, adifferential, and a drive shaft. Other components of transmission 120are possible. The drive shafts could include one or more axles thatcould be coupled to the one or more wheels/tires 121.

The wheels/tires 121 of vehicle 100 could be configured in variousformats, including a unicycle, bicycle/motorcycle, tricycle, orcar/truck four-wheel format. Other wheel/tire geometries are possible,such as those including six or more wheels. Any combination of thewheels/tires 121 of vehicle 100 may be operable to rotate differentiallywith respect to other wheels/tires 121. The wheels/tires 121 couldrepresent at least one wheel that is fixedly attached to thetransmission 120 and at least one tire coupled to a rim of the wheelthat could make contact with the driving surface. The wheels/tires 121could include any combination of metal and rubber. Other materials arepossible.

The sensor system 104 may include several elements such as a GlobalPositioning System (GPS) 122, ultrasonic sensors (not shown), aninertial measurement unit (IMU) 124, a radar 126, a laserrangefinder/LIDAR 128, a camera 130, a steering sensor 123, and athrottle/brake sensor 125. The sensor system 104 could also includeother sensors, such as those that may monitor internal systems of thevehicle 100 (e.g., O₂ monitor, fuel gauge, engine oil temperature, brakewear).

The GPS 122 could include a transceiver operable to provide informationregarding the position of the vehicle 100 with respect to the Earth. TheIMU 124 could include a combination of accelerometers and gyroscopes andcould represent any number of systems that sense position andorientation changes of a body based on inertial acceleration.Additionally, the IMU 124 may be able to detect a pitch and yaw of thevehicle 100. The pitch and yaw may be detected while the vehicle isstationary or in motion.

The radar 126 may represent a system that utilizes radio signals tosense objects, and in some cases their speed and heading, with respectto the local environment of the vehicle 100. Additionally, the radar 126may have a plurality of antennas configured to transmit and receiveradio signals. The laser rangefinder/LIDAR 128 could include one or morelaser sources, a laser scanner, and one or more detectors, among othersystem components. The laser rangefinder/LIDAR 128 could be configuredto operate in a coherent mode (e.g., using heterodyne detection) or inan incoherent detection mode. The camera 130 could include one or moredevices configured to capture a plurality of images of the environmentof the vehicle 100. The camera 130 could be a still camera or a videocamera.

The steering sensor 123 may represent a system that senses the steeringangle of the vehicle 100. In some embodiments, the steering sensor 123may measure the angle of the steering wheel itself. In otherembodiments, the steering sensor 123 may measure an electrical signalrepresentative of the angle of the steering wheel. Still, in furtherembodiments, the steering sensor 123 may measure an angle of the wheelsof the vehicle 100. For instance, an angle of the wheels with respect toa forward axis of the vehicle 100 could be sensed. Additionally, in yetfurther embodiments, the steering sensor 123 may measure a combination(or a subset) of the angle of the steering wheel, electrical signalrepresenting the angle of the steering wheel, and the angle of thewheels of vehicle 100.

The throttle/brake sensor 125 may represent a system that senses theposition of either the throttle position or brake position of thevehicle 100. In some embodiments, separate sensors may measure thethrottle position and brake position. In some embodiments, thethrottle/brake sensor 125 may measure the angle of both the gas pedal(throttle) and brake pedal. In other embodiments, the throttle/brakesensor 125 may measure an electrical signal that could represent, forinstance, an angle of a gas pedal (throttle) and/or an angle of a brakepedal. Still, in further embodiments, the throttle/brake sensor 125 maymeasure an angle of a throttle body of the vehicle 100. The throttlebody may include part of the physical mechanism that provides modulationof the energy source 119 to the engine/motor 118 (e.g., a butterflyvalve or carburetor). Additionally, the throttle/brake sensor 125 maymeasure a pressure of one or more brake pads on a rotor of vehicle 100.In yet further embodiments, the throttle/brake sensor 125 may measure acombination (or a subset) of the angle of the gas pedal (throttle) andbrake pedal, electrical signal representing the angle of the gas pedal(throttle) and brake pedal, the angle of the throttle body, and thepressure that at least one brake pad is applying to a rotor of vehicle100. In other embodiments, the throttle/brake sensor 125 could beconfigured to measure a pressure applied to a pedal of the vehicle, suchas a throttle or brake pedal.

The control system 106 could include various elements include steeringunit 132, throttle 134, brake unit 136, a sensor fusion algorithm 138, acomputer vision system 140, a navigation/pathing system 142, and anobstacle avoidance system 144. The steering unit 132 could represent anycombination of mechanisms that may be operable to adjust the heading ofvehicle 100. The throttle 134 could control, for instance, the operatingspeed of the engine/motor 118 and thus control the speed of the vehicle100. The brake unit 136 could be operable to decelerate the vehicle 100.The brake unit 136 could use friction to slow the wheels/tires 121. Inother embodiments, the brake unit 136 could convert the kinetic energyof the wheels/tires 121 to electric current.

A sensor fusion algorithm 138 could include, for instance, a Kalmanfilter, Bayesian network, or other algorithm that may accept data fromsensor system 104 as input. The sensor fusion algorithm 138 couldprovide various assessments based on the sensor data. Depending upon theembodiment, the assessments could include evaluations of individualobjects and/or features, evaluation of a particular situation, and/orevaluate possible impacts based on the particular situation. Otherassessments are possible.

The computer vision system 140 could include hardware and softwareoperable to process and analyze images in an effort to determineobjects, important environmental features (e.g., stop lights, road wayboundaries, etc.), and obstacles. The computer vision system 140 coulduse object recognition, Structure From Motion (SFM), video tracking, andother algorithms used in computer vision, for instance, to recognizeobjects, map an environment, track objects, estimate the speed ofobjects, etc.

The navigation/pathing system 142 could be configured to determine adriving path for the vehicle 100. The navigation/pathing system 142 mayadditionally update the driving path dynamically while the vehicle 100is in operation. In some embodiments, the navigation/pathing system 142could incorporate data from the sensor fusion algorithm 138, the GPS122, and known maps so as to determine the driving path for vehicle 100.

The obstacle avoidance system 144 could represent a control systemconfigured to evaluate potential obstacles based on sensor data andcontrol the vehicle 100 to avoid or otherwise negotiate the potentialobstacles.

Various peripherals 108 could be included in vehicle 100. For example,peripherals 108 could include a wireless communication system 146, atouchscreen 148, a microphone 150, and/or a speaker 152. The peripherals108 could provide, for instance, means for a user of the vehicle 100 tointeract with the user interface 116. For example, the touchscreen 148could provide information to a user of vehicle 100. The user interface116 could also be operable to accept input from the user via thetouchscreen 148. In other instances, the peripherals 108 may providemeans for the vehicle 100 to communicate with devices within itsenvironment.

In one example, the wireless communication system 146 could beconfigured to wirelessly communicate with one or more devices directlyor via a communication network. For example, wireless communicationsystem 146 could use 3G cellular communication, such as CDMA, EVDO,GSM/GPRS, or 4G cellular communication, such as WiMAX or LTE.Alternatively, wireless communication system 146 could communicate witha wireless local area network (WLAN), for example, using WiFi. In someembodiments, wireless communication system 146 could communicatedirectly with a device, for example, using an infrared link, Bluetooth,or ZigBee. Other wireless protocols, such as various vehicularcommunication systems, are possible within the context of thedisclosure. For example, the wireless communication system 146 couldinclude one or more dedicated short range communications (DSRC) devicesthat could include public and/or private data communications betweenvehicles and/or roadside stations.

The power supply 110 may provide power to various components of vehicle100 and could represent, for example, a rechargeable lithium-ion orlead-acid battery. In an example embodiment, one or more banks of suchbatteries could be configured to provide electrical power. Other powersupply materials and types are possible. Depending upon the embodiment,the power supply 110, and energy source 119 could be integrated into asingle energy source, such as in some all-electric cars.

Many or all of the functions of vehicle 100 could be controlled bycomputer system 112. Computer system 112 may include at least oneprocessor 113 (which could include at least one microprocessor) thatexecutes instructions 115 stored in a non-transitory computer readablemedium, such as the data storage 114. The computer system 112 may alsorepresent a plurality of computing devices that may serve to controlindividual components or subsystems of the vehicle 100 in a distributedfashion.

In some embodiments, data storage 114 may contain instructions 115(e.g., program logic) executable by the processor 113 to execute variousfunctions of vehicle 100, including those described herein in connectionwith FIG. 4. Data storage 114 may contain additional instructions aswell, including instructions to transmit data to, receive data from,interact with, and/or control one or more of the propulsion system 102,the sensor system 104, the control system 106, and the peripherals 108.

In addition to the instructions 115, the data storage 114 may store datasuch as roadway maps, path information, among other information. Suchinformation may be used by vehicle 100 and computer system 112 at duringthe operation of the vehicle 100 in the autonomous, semi-autonomous,and/or manual modes.

The vehicle 100 may include a user interface 116 for providinginformation to or receiving input from a user of vehicle 100. The userinterface 116 could control or enable control of content and/or thelayout of interactive images that could be displayed on the touchscreen148. Further, the user interface 116 could include one or moreinput/output devices within the set of peripherals 108, such as thewireless communication system 146, the touchscreen 148, the microphone150, and the speaker 152.

The computer system 112 may control the function of the vehicle 100based on inputs received from various subsystems (e.g., propulsionsystem 102, sensor system 104, and control system 106), as well as fromthe user interface 116. For example, the computer system 112 may utilizeinput from the sensor system 104 in order to estimate the outputproduced by the propulsion system 102 and the control system 106.Depending upon the embodiment, the computer system 112 could be operableto monitor many aspects of the vehicle 100 and its subsystems. In someembodiments, the computer system 112 may disable some or all functionsof the vehicle 100 based on signals received from sensor system 104.

The components of vehicle 100 could be configured to work in aninterconnected fashion with other components within or outside theirrespective systems. For instance, in an example embodiment, the camera130 could capture a plurality of images that could represent informationabout a state of an environment of the vehicle 100 operating in anautonomous mode. The state of the environment could include parametersof the road on which the vehicle is operating. For example, the computervision system 140 may be able to recognize the slope (grade) or otherfeatures based on the plurality of images of a roadway. Additionally,the combination of Global Positioning System 122 and the featuresrecognized by the computer vision system 140 may be used with map datastored in the data storage 114 to determine specific road parameters.Further, the radar unit 126 may also provide information about thesurroundings of the vehicle.

In other words, a combination of various sensors (and the computersystem 112 could interact to provide an indication of an input providedto control a vehicle or an indication of the surroundings of a vehicle.

The computer system 112 could carry out several determinations based onthe indications received from the output-indication sensors and the datarelated to the received signals. For example, the computer system 112could calculate a radar adjustment based on the motion of the vehicle.Additionally, the computer system 112 could calculate revised distanceand direction information from the received electromagnetic signal basedon the radar adjustment values.

In one scenario, the radar unit 126 may receive a plurality of radarsignals from a plurality of target objects within the field of view ofthe radar. Additionally, the radar unit 126 may transmit data relatingto the plurality of received radar signals to the computer system 112.Further, the computer system 112 may also receive data relating to themotion of the autonomous vehicle. For example, the computer system 112may receive an indication that vehicle is decelerating at a specificrate. Thus, the computer system 112 may calculate a radar adjustmentbased on the deceleration.

For example, if the vehicle is quickly decelerating, the front of thevehicle may pitch downward toward the street. The computer system 112may calculate a radar adjustment to compensate for the change in vehiclepitch. In this some embodiments, the radar adjustment may includeignoring the radar signals for a period of time. In another embodiment,the radar adjustment may include a weighting criteria applied to theradar signals. The weighting criteria may take many forms. In someembodiments, the weighting criteria may make the radar signals receivedduring the deceleration have less importance in calculations by thecomputer system 112. In other embodiments, the weighting criteria mayadjust the data received based on the radar signals in order tocompensate for a change in pitch of the radar antennas (i.e.mathematically calculate an approximation for the data received if thevehicle had not had a change in pitch).

Although FIG. 1 shows various components of vehicle 100, i.e., wirelesscommunication system 146, computer system 112, data storage 114, anduser interface 116, as being integrated into the vehicle 100, one ormore of these components could be mounted or associated separately fromthe vehicle 100. For example, data storage 114 could, in part or infull, exist separate from the vehicle 100. Thus, the vehicle 100 couldbe provided in the form of device elements that may be locatedseparately or together. The device elements that make up vehicle 100could be communicatively coupled together in a wired and/or wirelessfashion.

FIG. 2 shows a vehicle 200 that could be similar or identical to vehicle100 described in reference to FIG. 1. Depending on the embodiment,vehicle 200 could include a sensor unit 202, a wireless communicationsystem 204, a radar 206, a laser rangefinder 208, and a camera 210. Theelements of vehicle 200 could include some or all of the elementsdescribed for FIG. 1. Although vehicle 200 is illustrated in FIG. 2 as acar, other embodiments are possible. For instance, the vehicle 200 couldrepresent a truck, a van, a semi-trailer truck, a motorcycle, a golfcart, an off-road vehicle, or a farm vehicle, among other examples.

The sensor unit 202 could include one or more different sensorsconfigured to capture information about an environment of the vehicle200. For example, sensor unit 202 could include any combination ofcameras, radars, LIDARs, range finders, and acoustic sensors. Othertypes of sensors are possible. Depending on the embodiment, the sensorunit 202 could include one or more movable mounts that could be operableto adjust the orientation of one or more sensors in the sensor unit 202.In one embodiment, the movable mount could include a rotating platformthat could scan sensors so as to obtain information from each directionaround the vehicle 200. In another embodiment, the movable mount of thesensor unit 202 could be moveable in a scanning fashion within aparticular range of angles and/or azimuths. The sensor unit 202 could bemounted atop the roof of a car, for instance, however other mountinglocations are possible. Additionally, the sensors of sensor unit 202could be distributed in different locations and need not be collocatedin a single location. Some possible sensor types and mounting locationsinclude radar 206 and laser rangefinder 208.

The wireless communication system 204 could be located as depicted inFIG. 2. Alternatively, the wireless communication system 204 could belocated, fully or in part, elsewhere. The wireless communication system204 may include wireless transmitters and receivers that could beconfigured to communicate with devices external or internal to thevehicle 200. Specifically, the wireless communication system 204 couldinclude transceivers configured to communicate with other vehiclesand/or computing devices, for instance, in a vehicular communicationsystem or a roadway station. Examples of such vehicular communicationsystems include dedicated short range communications (DSRC), radiofrequency identification (RFID), and other proposed communicationstandards directed towards intelligent transport systems.

The camera 210 could be mounted inside a front windshield of the vehicle200. The camera 210 could be configured to capture a plurality of imagesof the environment of the vehicle 200. Specifically, as illustrated, thecamera 210 could capture images from a forward-looking view with respectto the vehicle 200. Other mounting locations and viewing angles ofcamera 210 are possible. The camera 210 could represent one or morevisible light cameras. Alternatively or additionally, camera 210 couldinclude infrared sensing capabilities. The camera 210 could haveassociated optics that could be operable to provide an adjustable fieldof view. Further, the camera 210 could be mounted to vehicle 200 with amovable mount that could be operable to vary a pointing angle of thecamera 210.

FIG. 3 illustrates a scenario 300 involving a vehicle 302 traveling downa roadway 304. A vehicle 302 could be operating in an autonomous mode.Further, the vehicle 302 may be configured with a radar unit 310. Theradar unit 310 may be configured with a plurality of antenna elements.In the particular embodiment shown in FIG. 3, the radar unit 310includes an array of four antennas. A schematic view of antennas CH1,CH2, CH3, and CH4 is shown to the right of vehicle 302 in FIG. 3. Asshown, the antennas are spaced apart with an equal distance between eachadjacent antenna. However, the system and methods disclose herein mayalso be used with radar systems with non-equal antenna spacing. Further,the radar unit 310 may contain a processor that receives the signalsfrom each antenna and coverts the plurality of signals into data.

In the example shown, the antenna array transmits a radio signal andreceives a portion of the transmitted radio signal that has reflectedfrom an object in the environment of vehicle 302. The reflected signalis received at an angle α to the antenna array. The angle α may beassumed to be the same for each element of the antenna array due to therelatively narrow antenna spacing compared to the distance to thereflection target(s).

In one example of FIG. 3, the vehicle may be traveling in the directionindicated by the arrow 306. As the vehicle is traveling, sensors (asdescribed with respect to FIGS. 1 and 2) may provide information aboutthe vehicle's movement to a processor in the vehicle. In one embodiment,as the vehicle moves forwards, the signals reflected back to thevehicle, may seem to have a relative motion to them despite the objectscausing the signals to reflect being stationary. For example, the angleα may appear to be increasing as the vehicle moves forward. The radarunit 310 may contain a processor that converts the received signals intodata representative of the received signals.

The processor may receive both data based on the received signals anddata from the sensors indicating the vehicle is in motion. The processorin the autonomous vehicle determines the distance and the angle toobjects that are reflecting the received signals back to the radarsystem. Further, the processor may also determine an object velocity ofthe objects that are reflecting the received signals back to the radarsystem. Additionally, the processor determines a radar adjustment basedon the movement of the vehicle. In this instance, the processor maydetermine that the motion of the vehicle, not the movement of theobjects causing the reflection, causes the apparent change in angle ofthe reflections. Thus, the processor may adjust the data based on thereceived signals to indicate the objects causing the reflections arestationary. Additionally, the movement of the vehicle may also cause anapparent change in the object velocity of the objects that arereflecting the received signals back to the radar system. The radarsystem may also correct for the apparent change in velocity.

In some example embodiments, the radar system may operate with anassociated signal processing mode. The data may be adjusted based on amode of operation as well. In one embodiment, the radar system may usean adaptive algorithm selection mode. In this mode, the radar system mayadjust various parameters of the radar system during operation. Theradar may change parameters such as beam widths, phasing of radarelements, etc. to produce a desired result. While operating in theadaptive algorithm selection mode, the radar system may use movementdata to further adjust parameters of the radar system. For example, theradar system may change how the radar collects incoming signals mode tominimize impacts of motion data related sidelobes. Additionally, theradar system may adjust heterodyne mixing plan to attempt to improverejection of motion data errors in intermediate frequency (IF)processing. Further, the radar system may use adaptive beam steeringbased on vehicle yaw and pitch.

In another example embodiment, the radar system may operate in an objectdetection mode. While operating in the object detection mode, the radarsystem may use movement data to further adjust parameters of the radarsystem. The radar system may apply a correction factor added to a Polarto Cartesian mapping function for to correct the detected objectlocation and velocity. Additionally, the radar system may use platformvibration data to predict spur locations, and limit their affect onobject detection.

In yet another example embodiment, the radar system may operate in adirection of arrival estimation mode. While operating in the directionof arrival estimation mode, the radar system may use movement data tofurther adjust parameters of the radar system. For example, the radarsystem may modify the inverse relationship between the vehicle'sacceleration and a detection/non-detection weight applied by the radarsystem. In a still further embodiment, the radar system may operate in atarget tracking mode. In target tracking mode, the radar system maymodify the inverse relationship between the vehicle's acceleration and adetection/non-detection weight applied by the radar system. Theassociated signal processing modes and how each may be modified based onthe movement data are given as examples. Other modes may be used, andmodified, based on the methods disclosed herein.

In another example of FIG. 3, the vehicle may be traveling in thedirection indicated by the arrow 306. As the vehicle is traveling, thevehicle may decrease in speed. As the vehicle decreases in speed, thefront (or nose) of the vehicle may tilt (or pitch) down toward theground. As the vehicle pitches forwards, the signals reflected back tothe vehicle, may seem to have moved vertically upward (i.e. increase inaltitude above the horizon) despite the objects causing the signals toreflect being stationary. For example, signals that were reflected alongthe horizon line before the vehicle pitched forward may appear to becoming from a higher altitude than the horizon.

Similar to the first embodiment, the processor will receive both databased on the received signals and data from the sensors indicating thevehicle is in motion. The processor in the autonomous vehicle determinesthe distance and the angle to objects that are reflecting the receivedsignals back to the radar system. Further, the processor may alsodetermine an object velocity of the objects that are reflecting thereceived signals back to the radar system. Additionally, the processordetermines a radar adjustment based on the movement of the vehicle. Inthis instance, the processor may determine that the motion of thevehicle, not the movement of the objects causing the reflection, causesthe apparent change in vertical of the reflections. Thus, the processormay adjust the data based on the received signals to indicate that theobjects causing the reflections are stationary.

However, in some additional embodiments, the pitch (or other movement)of the vehicle may occur to such an extent that the reflected signalsare no longer received by the antennas at all. For example, a radarsystem may have a beam width in a specific direction of only 5 degrees.If the vehicle's pitch is greater than 5 degrees, objects may appear tobe outside the beam width. Thus, these objects may not reflect signalsback to the vehicle. In this embodiment, the processor may adjust thedata by temporarily ignoring the lack of reflections received by theantenna. The processor may mathematically predict where the reflectionswould be if they were within the antenna beam width. Further, theprocessor may use the mathematical predictions for the reflectionsduring the period where the vehicle's pitch is greater than a thresholdassociated with the radar beam width. Typically, the acceleration ordeceleration of a vehicle is only temporary. Thus, the mathematicalpredictions could be discontinued after the temporary acceleration ordeceleration.

In yet another embodiment, the pitch (or other movement) of the vehiclemay be to an extent that the reflected signals are received withrelatively low power. For example, as the reflected signals move nearthe edge of the radar system beam width, the radar system may be lessefficient at receiving signals. In one example, as the vehicle's pitchapproaches 5 degrees, the reflections may appear much weaker. Thus, atypical radar system may incorrectly assume the objects causing thereflections are further away. In this embodiment, the processor mayadjust the data by temporarily increasing a weighting on reflectionsreceived by the antenna. The processor may mathematically increase aweighting factor as if the reflections were within the optimal portionof the antenna beam width. Further, the processor may use themathematical weighting factor for the reflections during the periodwhere the vehicle's pitch is within a range of the threshold associatedwith the radar beam width. Typically, the acceleration or decelerationof a vehicle is only temporary. Thus, the use of the weighting factorcould be discontinued after the temporary acceleration or deceleration.

In a further embodiment, the speed vehicle may cause artifacts in thereceived signals. For example, at a specific velocity, the vehicle mayexperience a vibration. This vibration may manifest as a disturbance inthe received signals. For example, the vibration may cause a periodicvariance in the received signal. In this embodiment, the processor mayadjust the data by temporarily adjusting a weighting on reflectionsreceived by the antenna. The processor may mathematically adjust theweighting factor to mitigate the variations caused by the vehicletraveling at a specific speed (and the associated vibrations in thisexample). In some embodiments, the received signals may be filtered witha filter to remove the disturbances. Further, the processor may use themathematical weighting factor for the reflections during the periodwhere the velocity of the vehicle causes disturbances. Typically,disturbances in the received signals are only temporary. Thus, use ofthe weighting factor could be discontinued after the temporarydisturbance.

3. Example Methods

A method 400 is provided for receiving data representative of anelectromagnetic signal, receiving an indication of a movement of thevehicle, determining a movement parameter based the indication of themovement of the vehicle, and recovering the distance and directioninformation from the electromagnetic signal, based on the movementparameter. The method could be performed using any of the apparatusshown in FIGS. 1-3 and described above; however, other configurationscould be used. FIG. 4 illustrates the steps in an example method,however, it is understood that in other embodiments, the steps mayappear in different order and steps could be added, subtracted, ormodified. Additionally, the steps may be performed in a linear manner(as shown) or may be performed in a parallel manner (not shown).

Step 402 includes receiving data representative of an electromagneticsignal. The vehicle is configured with a radar system. The vehicledescribed in this method could be the vehicle 100 and/or vehicle 200 asillustrated and described in reference to FIGS. 1 and 2, respectively.Receiving data representative of an electromagnetic signal could includereceiving radio signals that are reflected from one or more objects inthe field of view of the radar system. A processor in the radar systemmay convert the received radio signals into data to relay for furtherprocessing. For example, the radar system may transmit a signal andreceive a set of reflected signals back. The radar system may furtheridentify distance and direction information to each object that causesreflections back to the vehicle. Depending upon the embodiment, thereflected signals may be processed fully or in part by a server andcommunicated to the vehicle.

Step 404 includes receiving an indication of a movement of the vehicle.One or more output-indication sensors could measure the movement of thevehicle. The vehicle may speed up, slow down, turn, change course, orkeep the same movement as part of the output. Additionally, the vehiclemovement may cause a responsive change in orientation of the vehicle.For example, the vehicle speeding up, slowing down, or turning may alsocause a responsive change in the pitch or yaw of the vehicle.Additionally, the indication of a movement of the vehicle may be thespeed, acceleration, heading, or any other indicator of the motion (orlack thereof) of the vehicle. The indication of a movement of thevehicle could be received from at least one output-indication sensor.Additionally, the vehicle may be stopped, thus the output may indicativeof the vehicle having no motion. Other types of indication of an outputof the vehicle are possible.

Step 406 includes determining a movement parameter based the indicationof the movement of the vehicle. The movement parameter could correspondto an adjustment of the data received in step 402 that accounts for themovement of the vehicle. Possible movement parameters could includeadjustments based on any combination of a speed, a rate of change ofspeed (acceleration), a heading, or any other indicator of the motion(or lack thereof) of the vehicle associated with driving on or off aroadway. For example, a vehicle may be traveling at 15 miles per hourand slow down to stop at a stop sign. As the vehicle decreases in speed,the front (or nose) of the vehicle may tilt (or pitch) down toward theground. As the vehicle pitches forwards, the signals reflected back tothe vehicle, appear to have moved vertically upward (i.e. increase inaltitude above the horizon) despite the objects causing the signals toreflect being stationary. Thus, the movement parameter may be anadjustment to the data representative of an electromagnetic signal tomake the reflections appear as if they have not moved relative to theradar. In some embodiments, the movement parameter may be called a radaradjustment.

In other embodiments, the vehicle may turn to the left or right. Due tothe turning motion of the vehicle, the signals reflected back to thevehicle, appear to have responsively moved to the right or to the left.The movement parameter may be an adjustment to the data representativeof an electromagnetic signal to make the reflections appear as if theyhave not moved relative to the radar. In yet another embodiment, themovement of the vehicle may cause the vehicle to experience a vibration.This vibration may manifest as a disturbance in the received signals.For example, the vibration may cause a periodic variance in the receivedsignal. The movement parameter may be an adjustment to the datarepresentative of an electromagnetic signal to remove the periodvariance cause by the vibration.

Step 408 includes recovering the distance and direction information fromthe electromagnetic signal, based on the movement parameter. Thecomputer system of the vehicle could alter the received datarepresentative of an electromagnetic signal based on the determinedmovement parameter. In some embodiments, recovering the distance anddirection information from the electromagnetic signal based on themovement parameter calculates what the distance and directioninformation from the radar system would be if the vehicle was notmoving. In another embodiments, recovering the distance and directioninformation from the electromagnetic signal based on the movementparameter calculates what the distance and direction information fromthe radar system would be if the vehicle did not change its movement.

A processor within the vehicle may recover the distance and datainformation. In some embodiments, there is a mathematical relationbetween the determined movement parameter and the distance and datainformation. For example, the distance and data information may beretrieved by applying a weighting determined at step 406 to the dataprovided at step 402. Other methods may be used to retrieve the distanceand data information based on the specific embodiment. For example, themovement parameter determined at step 406 and the data provided at step402 may take different formats depending on the specific embodiment.However, the methods and systems presented herein are not dependent onthe format of the various signals.

Example methods, such as method 400 of FIG. 4, may be carried out inwhole or in part by the vehicle and its subsystems. Accordingly, examplemethods could be described by way of example herein as being implementedby the vehicle. However, it should be understood that an example methodmay be implemented in whole or in part by other computing devices. Forexample, an example method may be implemented in whole or in part by aserver system, which receives data from a device such as thoseassociated with the vehicle. Other examples of computing devices orcombinations of computing devices that can implement an example methodare possible.

It will be understood that there are other similar methods that coulddescribe receiving data representative of an electromagnetic signal,receiving an indication of a movement of the vehicle, determining amovement parameter based the indication of the movement of the vehicle,and recovering the distance and direction information from theelectromagnetic signal, based on the movement parameter. Those similarmethods are implicitly contemplated herein.

In some embodiments, the disclosed methods may be implemented ascomputer program instructions encoded on a non-transitorycomputer-readable storage media in a machine-readable format, or onother non-transitory media or articles of manufacture. FIG. 5 is aschematic illustrating a conceptual partial view of an example computerprogram product that includes a computer program for executing acomputer process on a computing device, arranged according to at leastsome embodiments presented herein.

In one embodiment, the example computer program product 500 is providedusing a signal bearing medium 502. The signal bearing medium 502 mayinclude one or more programming instructions 504 that, when executed byone or more processors may provide functionality or portions of thefunctionality described above with respect to FIGS. 1-4. In someexamples, the signal bearing medium 502 may encompass acomputer-readable medium 506, such as, but not limited to, a hard diskdrive, a Compact Disc (CD), a Digital Video Disk (DVD), a digital tape,memory, etc. In some implementations, the signal bearing medium 502 mayencompass a computer recordable medium 508, such as, but not limited to,memory, read/write (R/W) CDs, R/W DVDs, etc. In some implementations,the signal bearing medium 502 may encompass a communications medium 510,such as, but not limited to, a digital and/or an analog communicationmedium (e.g., a fiber optic cable, a waveguide, a wired communicationslink, a wireless communication link, etc.). Thus, for example, thesignal bearing medium 502 may be conveyed by a wireless form of thecommunications medium 510.

The one or more programming instructions 504 may be, for example,computer executable and/or logic implemented instructions. In someexamples, a computing device such as the computer system 112 of FIG. 1may be configured to provide various operations, functions, or actionsin response to the programming instructions 504 conveyed to the computersystem 112 by one or more of the computer readable medium 506, thecomputer recordable medium 508, and/or the communications medium 510.

The non-transitory computer readable medium could also be distributedamong multiple data storage elements, which could be remotely locatedfrom each other. The computing device that executes some or all of thestored instructions could be a vehicle, such as the vehicle 200illustrated in FIG. 2. Alternatively, the computing device that executessome or all of the stored instructions could be another computingdevice, such as a server.

The above detailed description describes various features and functionsof the disclosed systems, devices, and methods with reference to theaccompanying figures. While various aspects and embodiments have beendisclosed herein, other aspects and embodiments will be apparent. Thevarious aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A system comprising: an antenna configured toreceive electromagnetic signals, wherein each electromagnetic signalprovides distance and direction information for at least one object inan environment of an autonomous vehicle; at least one sensor configuredto provide an output based on a movement of the autonomous vehiclewherein the movement includes a front end of the vehicle pitching downtowards the ground below the vehicle as a result of a decrease in speedof the vehicle; and at least one processor configured to: prior to themovement, identify a first object and a second object from first signalsof the electromagnetic signals; use the distance and directioninformation of the second signals the electromagnetic signals toidentify and determine an object velocity for a first object indicatingthat the first object is moving relative to the vehicle; determine amovement parameter based on the output of the at least one sensor,wherein the movement parameter is an adjustment value that compensatesfor the movement; determine that the first object is stationary relativeto the vehicle based on the movement parameter and the object velocity;use the determination that the first object is stationary to control thevehicle; determine that the second electromagnetic signals do notprovide current distance and direction information for the secondobject; determine that the movement parameter meets a threshold value;and when the movement parameter is determined to meet the thresholdvalue, temporarily ignoring, by the computing system, the determinationthat the second electromagnetic signals do not provide distance anddirection information for the second object when controlling thevehicle.
 2. The autonomous vehicle of claim 1, further comprising aplurality of antennas.
 3. The autonomous vehicle of claim 2, wherein theplurality of antennas form an array.
 4. A method comprising: receivingradar data representative of electromagnetic signals, wherein eachelectromagnetic signal provides distance and direction information forat least one object in an environment of an autonomous vehicle; prior tothe movement, identify a first object and a second object from firstsignals of the electromagnetic signals; using the distance and directioninformation of second electromagnetic signals to determine an objectvelocity for the first object indicating that the first object is movingrelative to the vehicle relative to the vehicle; receiving movement datarepresentative a movement of the autonomous vehicle wherein the movementincludes a front end of the vehicle pitching down towards the groundbelow the vehicle as a result of a decrease in speed of the vehicle;determining, by a computer system having at least one processor, amovement parameter including an adjustment value to compensate for themovement based on the movement data; and determining, by the computersystem, that the first object is stationary relative to the vehiclebased on the movement parameter and the velocity; determine that thesecond electromagnetic signals do not provide current distance anddirection information for the second object; determine that the movementparameter meets a threshold value; using the determination that the atleast one object is stationary to control the vehicle; and when themovement parameter is determined to meet the threshold value,temporarily ignoring, by the computing system, the determination thatthe second electromagnetic signals do not provide distance and directioninformation for the second object when controlling the vehicle.
 5. Themethod of claim 4, wherein receiving radar data representative of anelectromagnetic signal further comprising receiving radar datarepresentative of a plurality of electromagnetic signals, wherein eachelectromagnetic signal is received by a respective antenna in aplurality of antennas.
 6. The method of claim 5, wherein the pluralityof antennas form an array.
 7. An article of manufacture including atangible non-transitory computer-readable medium havingcomputer-readable instructions encoded thereon, the instructionscomprising: instructions for, prior to the movement, identify a firstobject and a second object from first signals of the electromagneticsignals; instructions for using the distance and direction informationof second electromagnetic signals to determine an object velocity forthe first object indicating that the first object is moving relative tothe vehicle relative to the vehicle; instructions for receiving movementdata representative of a movement of the autonomous vehicle wherein themovement includes a front end of the vehicle pitching down towards theground below the vehicle as a result of a decrease in speed of thevehicle; instructions for determining a movement parameter including anadjustment value to compensate for the movement based on the movementdata; and instructions for determining that the second electromagneticsignals do not provide current distance and direction information forthe second object; instructions for determining that the movementparameter meets a threshold value; instructions for determining that thefirst object is stationary relative to the vehicle based on the movementparameter and the velocity; and instructions for when the movementparameter is determined to meet the threshold value, temporarilyignoring, by the computing system, the determination that the secondelectromagnetic signals do not provide distance and directioninformation for the second object when controlling the vehicle.
 8. Themethod of claim 4, further comprising when the movement parameter isdetermined to meet the threshold value, estimating, by the computingsystem, current distance and direction information for the secondobject; and using the estimate to control the vehicle.
 9. The method ofclaim 7, wherein the threshold value corresponds to a width of a radarbeam used to collect the radar data.
 10. The system of claim 1, furthercomprising the autonomous vehicle.
 11. The system of claim 1, whereinthe at least one processor is further configured to: when the movementparameter is determined to meet the threshold value, estimate currentdistance and direction information for the second object; and use theestimate to control the vehicle.
 12. The system of claim 1, wherein thethreshold value corresponds to a width of a radar beam used to collectthe radar data.
 13. The article of manufacture of claim 7, wherein theinstructions further comprise: instructions for, when the movementparameter is determined to meet the threshold value, estimating, by thecomputing system, current distance and direction information for thesecond object, and instructions for using the estimate to control thevehicle.
 14. The article of manufacture of claim 7, wherein thethreshold value corresponds to a width of a radar beam used to collectthe radar data.
 15. The system of claim 1, wherein the at least oneprocessor is further configured to temporarily ignore the determinationthat the second electromagnetic signals do not provide distance anddirection information for the second object when controlling the vehiclewhile the pitch of the front end of the vehicle exceeds a thresholdassociated with a width of a radar beam.
 16. They system of claim 1,wherein the threshold value corresponds to a width of a radar beam usedto collect the radar data in a direction corresponding to a direction ofthe pitching of the front end of the vehicle.
 17. The method of claim 4,wherein the method further comprises, temporarily ignoring thedetermination that the second electromagnetic signals do not providedistance and direction information for the second object whencontrolling the vehicle while the pitch of the front end of the vehicleexceeds a threshold associated with a width of a radar beam.
 18. Theymethod of claim 4, wherein the threshold value corresponds to a width ofa radar beam used to collect the radar data in a direction correspondingto a direction of the pitching of the front end of the vehicle.
 19. Thearticle of manufacture claim 7, wherein the instructions furthercomprise instructions for temporarily ignoring the determination thatthe second electromagnetic signals do not provide distance and directioninformation for the second object when controlling the vehicle while thepitch of the front end of the vehicle exceeds a threshold associatedwith a width of a radar beam.
 20. They article of manufacture claim 7,wherein the threshold value corresponds to a width of a radar beam usedto collect the radar data in a direction corresponding to a direction ofthe pitching of the front end of the vehicle.